Finding and understanding pedal misapplication crashes using a deep learning natural language model-Reference-Cited by-同舟云学术

Finding and understanding pedal misapplication crashes using a deep learning natural language model

Published:2021-10-19 Issue:sup1 Volume:22 Page:S169-S172
ISSN:1538-9588
Container-title:Traffic Injury Prevention
language:en
Short-container-title:Traffic Injury Prevention

Author:

Bareiss Max¹^ORCID,Smith Colin¹,Gabler Hampton C.¹

Affiliation:

1. Department of Biomedical Engineering, Virginia Tech, Blacksburg, Virginia

Funder

Collaborative Safety Research Center

Toyota Motor Corporation

Publisher

Informa UK Limited

Subject

Public Health, Environmental and Occupational Health,Safety Research

Link

https://www.tandfonline.com/doi/pdf/10.1080/15389588.2021.1982616

Reference6 articles.

1. Devlin J, Chang M-W, Lee K, Toutanova K. 2018. BERT: pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805 [cs].

2. Hugging Face. 2021. bert-large-uncased-whole-word-masking. Hugging Face [accessed 2021 Mar 22]. https://huggingface.co/bert-large-uncased-whole-word-masking.

3. Lococo KH, Staplin L, Martell CA, Sifrit KJ. 2012. Pedal application errors (No. DOT HS 811 597).

4. null

5. Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser Ł, Polosukhin I. 2017. Attention is all you need. Paper presented at the 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, p. 11.

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